Practice of Epidemiologic Analysis [ESP65]
Monday to Friday (5 mornings)
Prof. Kamran Ikram
Erasmus MC, Rotterdam NL
No prior knowledge is required although understanding of basic epidemiology is helpful.
Detailed information about this course:
Faculty: Prof. Kamran Ikram, MD PhD and F.J.A van Rooij
Formulating a research question, considering the design of a study, collecting data, analyzing data and reporting of findings are crucial steps in any scientific research. However, other aspects that are equally important often receive less attention and in some cases may even be neglected. These topics include:
- Data Quality;
- Data Presentation;
- Data Documentation.
Specific topics covered include Data preparation, Missingness, Data restructuring (e.g. categorization, normalization, standardization), Visualisation. Most topics discussed in this course lie at the cross-roads of Epidemiology and Biostatistics and cover issues that are typically faced by starting researchers. For starting scientists it is important to realize that these aspects are an integral part of scientific research and form the basis of the scientific integrity of any research project. In this course, the first three days will be devoted to each of these three aspects: Quality, Presentation and Documentation. These will include lectures covering both theoretical aspects and live demonstrations with R and R Markdown. Furthermore, on the fourth day, the students will get an opportunity to gain some initial experience with hands-on exercises in the practical. Finally, on the last day, there will be lectures on selected topics, that are increasingly dominating the scientific landscape, but are usually covered from a statistical, mathematical or engineering perspective. Here, these topics will be discussed from the point of view of an epidemiologist, as there is much overlap with the practice of epidemiologic analysis!
- To gain better understanding of issues related to Data Quality, Data Presentation and Data Documentation.
- To enable students to translate the theoretical insights into practical tools, which they can immediately implement in their own research.
The course is particularly intended for participants who have completed their data collection and move towards
their first data analysis.
Reduction on fees
PLEASE NOTE: This does not apply to the fee of the research master programmes (120 EC points)
No fees are charged for Erasmus MC PhD candidates, provided they have an account in Hora Finita, the Erasmus University PhD registration system. When submitting the application, you can state that someone else pays your tuition fee.
In case of cancellation or no show, the cancellation policy applies based on the full course fee.
25% reduction for all (international) PhD candidates without formal appointment at Erasmus MC
Upon receipt of your application you will receive a request to upload proof of enrollment as a PhD candidate.